Advertisement

The journal of nutrition, health & aging

, Volume 21, Issue 10, pp 1233–1239 | Cite as

Model construction for biological age based on a cross-sectional study of a healthy Chinese han population

  • W. Zhang
  • L. Jia
  • G. Cai
  • F. Shao
  • H. Lin
  • Z. Liu
  • F. Liu
  • D. Zhao
  • Z. Li
  • X. Bai
  • Z. Feng
  • XueFeng SunEmail author
  • Xiang-Mei ChenEmail author
Article

Abstract

Objectives

Biological age (BA) has been proposed to evaluate the aging status in an objective way instead of chronological age (CA). The purpose of our study is to construct a more precise formula of BA in the cross-sectional study based on a largest-ever sample of our studies. This formula aims at better evaluation of body function and exploring the disciplines of aging in different genders and age stages.

Methods

A total of 1,373 healthy Chinese Han (age range, 19-93 years) were recruited from five cities in China, including 581 males and 792 females. Physical examination, blood routine, blood chemistry, and other lab tests were performed to obtain a total of 74 clinical variables. Then, the principal component analysis (PCA) was used to select variables and estimate BA. The BA formula was further validated in a population with some diseases (n=266), including cardiovascular diseases, type 2 diabetes, kidney diseases, pulmonary diseases, cancer and disorders in nervous system.

Results

The BA formula was constructed as follows: BA = 0.358 (pulse pressure) + 0.258 (trail making test)–11.552 (mitral valve E/A peak) + 26.383 (minimum intima-media thickness) + 31.965 (Cystatin C) + 0.163 (CA)–3.902. In validation of the formula, BAs of patients were older than those of healthy persons. The BA accelerates faster in the middle-aged population than in the elderly population (>75 years old).

Conclusion

This BA formula can reflect health condition changes of aging better than CA in a Chinese Han population.

Keywords

Biological age chronological age principal component analysis 

References

  1. 1.
    Zhang G, Li J, Purkayastha S, Tang Y, Zhang H, Yin Y, et al. Hypothalamic programming of systemic ageing involving IKK-beta, NF-kappaB and GnRH. Nature. 2013;497(7448):211–6.CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Yabuta S, Masaki M, Shidoji Y. Associations of Buccal Cell Telomere Length with Daily Intake of beta-Carotene or alpha-Tocopherol Are Dependent on Carotenoid Metabolism-related Gene Polymorphisms in Healthy Japanese Adults. J Nutr Health Aging. 2016;20(3):267–74.CrossRefPubMedGoogle Scholar
  3. 3.
    Rabassa M, Zamora-Ros R, Andres-Lacueva C, Urpi-Sarda M, Bandinelli S, Ferrucci L, et al. Association between Both Total Baseline Urinary and Dietary Polyphenols and Substantial Physical Performance Decline Risk in Older Adults: A 9-year Follow-up of the InCHIANTI Study. J Nutr Health Aging. 2016;20(5):478–85.CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Gunn DA, Rexbye H, Griffiths CE, Murray PG, Fereday A, Catt SD, et al. Why some women look young for their age. PloS one. 2009;4(12):e8021.CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Nakamura E, Moritani T, Kanetaka A. Biological age versus physical fitness age. Eur J Appl Physiol Occup Physiol. 1989;58(7):778–85.CrossRefPubMedGoogle Scholar
  6. 6.
    Nakamura E, Moritani T, Kanetaka A. Biological age versus physical fitness age in women. Eur J Appl Physiol Occup Physiol. 1990;61(3-4):202–8.CrossRefPubMedGoogle Scholar
  7. 7.
    Kimura M, Mizuta C, Yamada Y, Okayama Y, Nakamura E. Constructing an index of physical fitness age for Japanese elderly based on 7-year longitudinal data: sex differences in estimated physical fitness age. Age. 2012;34(1):203–14.CrossRefPubMedGoogle Scholar
  8. 8.
    Nakamura E, Miyao K. Further evaluation of the basic nature of the human biological aging process based on a factor analysis of age-related physiological variables. J Gerontol A Biol Sci Med Sci. 2003;58(3):196–204.CrossRefPubMedGoogle Scholar
  9. 9.
    Levine ME. Modeling the rate of senescence: can estimated biological age predict mortality more accurately than chronological age? J Gerontol A Biol Sci Med Sci. 2013;68(6):667–74.Google Scholar
  10. 10.
    Belsky DW, Caspi A, Houts R, Cohen HJ, Corcoran DL, Danese A, et al. Quantification of biological aging in young adults. Proc Nati Acad Sci U S A. 2015;112(30):E4104–10.CrossRefGoogle Scholar
  11. 11.
    Cho IH, Park KS, Lim CJ. An empirical comparative study on biological age estimation algorithms with an application of Work Ability Index (WAI). Mech Ageing Dev. 2010;131(2):69–78.CrossRefPubMedGoogle Scholar
  12. 12.
    Mekli K, Marshall A, Nazroo J, Vanhoutte B, Pendleton N. Genetic variant of Interleukin-18 gene is associated with the Frailty Index in the English Longitudinal Study of Ageing. Age Ageing. 2015;44(6):938–42.CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Nakamura E, Miyao K, Ozeki T. Assessment of biological age by principal component analysis. Mech Ageing Dev. 1988;46(1-3):1–18.CrossRefPubMedGoogle Scholar
  14. 14.
    Development of Social Service Statistical Bulletin of 2014. China’s Ministry of Civil Affairs, 2014.Google Scholar
  15. 15.
    Zhang WG, Bai XJ, Sun XF, Cai GY, Bai XY, Zhu SY, et al. Construction of an integral formula of biological age for a healthy Chinese population using principle component analysis. J Nutr Health Aging. 2014;18(2):137–42.CrossRefPubMedGoogle Scholar
  16. 16.
    Bai X, Han L, Liu Q, Shan H, Lin H, Sun X, et al. Evaluation of biological aging process -a population-based study of healthy people in China. Gerontology. 2010;56(2):129–40.CrossRefPubMedGoogle Scholar
  17. 17.
    Baker GT, Sprott RL. Biomarkers of aging. Exp Gerontol 1988; 23: 223–239.CrossRefPubMedGoogle Scholar
  18. 18.
    Jee H, Jeon BH, Kim YH, Kim HK, Choe J, Park J, et al. Development and application of biological age prediction models with physical fitness and physiological components in Korean adults. Gerontology. 2012;58(4):344–53.CrossRefPubMedGoogle Scholar
  19. 19.
    Ueno LM, Yamashita Y, Moritani T, Nakamura E. Biomarkers of aging in women and the rate of longitudinal changes. J Physiol Anthropol Appl Human Sci. 2003;22(1):37–46.CrossRefPubMedGoogle Scholar
  20. 20.
    Nakamura E, Miyao K. Sex differences in human biological aging. J Gerontol A Biol Sci Med Sci. 2008;63(9):936–44.CrossRefPubMedGoogle Scholar
  21. 21.
    Zhang WG, Zhu SY, Bai XJ, Zhao DL, Jian SM, Li J, et al. Select aging biomarkers based on telomere length and chronological age to build a biological age equation. Age. 2014;36(3):9639.CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Lopez-Giacoman S, Madero M. Biomarkers in chronic kidney disease, from kidney function to kidney damage. World J Nephrol. 2015;4(1):57–73.CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Ross JM, Stewart JB, Hagstrom E, Brene S, Mourier A, Coppotelli G, et al. Germline mitochondrial DNA mutations aggravate ageing and can impair brain development. Nature. 2013;501(7467):412–5.CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Katsimpardi L, Litterman NK, Schein PA, Miller CM, Loffredo FS, Wojtkiewicz GR, et al. Vascular and neurogenic rejuvenation of the aging mouse brain by young systemic factors. Science. 2014;344(6184):630–4.CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Shafto MA, Tyler LK. Language in the aging brain: the network dynamics of cognitive decline and preservation. Science. 2014;346(6209):583–7.CrossRefPubMedGoogle Scholar
  26. 26.
    Nakamura E, Miyao K. A method for identifying biomarkers of aging and constructing an index of biological age in humans. J Gerontol A Biol Sci Med Sci. 2007;62(10):1096–105.CrossRefPubMedGoogle Scholar
  27. 27.
    Park J, Cho B, Kwon H, Lee C. Developing a biological age assessment equation using principal component analysis and clinical biomarkers of aging in Korean men. Arch Gerontol Geriatr. 2009;49(1):7–12.CrossRefPubMedGoogle Scholar
  28. 28.
    Hayflick, Leonard. 2003. Has anyone ever died of old age? International Longevity Center, USA.Google Scholar
  29. 29.
    Schramme T. ‘I hope that I get old before I die’: ageing and the concept of disease. Theor Med and Bioeth. 2013;34(3):171–87.CrossRefGoogle Scholar
  30. 30.
    Comfort A. Physiology, homoeostasis and ageing. Gerontologia. 1968;14(4):224–34.CrossRefPubMedGoogle Scholar
  31. 31.
    Comfort A. Test-battery to measure ageing-rate in man. Lancet. 1969;2(7635):1411–4.CrossRefPubMedGoogle Scholar
  32. 32.
    Doyle YG, Mc Kee M, Sherriff M. A model of successful ageing in British populations. Eur J Public Health. 2012;22(1):71–6.CrossRefPubMedGoogle Scholar

Copyright information

© Serdi and Springer-Verlag France 2017

Authors and Affiliations

  • W. Zhang
    • 1
  • L. Jia
    • 2
  • G. Cai
    • 1
  • F. Shao
    • 3
  • H. Lin
    • 4
  • Z. Liu
    • 5
  • F. Liu
    • 6
  • D. Zhao
    • 1
  • Z. Li
    • 1
  • X. Bai
    • 7
  • Z. Feng
    • 1
  • XueFeng Sun
    • 1
    • 8
    Email author
  • Xiang-Mei Chen
    • 1
    • 8
    Email author
  1. 1.Department of NephrologyChinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney DiseasesBeijingChina
  2. 2.Department of NephrologySecond Hospital of Jilin UniversityChangchun, Jilin ProvinceChina
  3. 3.Department of NephrologyPeople’s Hospital of Henan ProvinceZhengzhou, Henan ProvinceChina
  4. 4.Department of NephrologyFirst Affiliated Hospital of Dalian Medical UniversityDalian, Liaoning ProvinceChina
  5. 5.Department of NephrologyFirst Affiliated Hospital of Zhengzhou UniversityZhengzhou, Henan ProvinceChina
  6. 6.Department of Nephrology, Second Xiangya HospitalCentral South UniversityChangsha, Hunan ProvinceChina
  7. 7.Department of Gerontology and GeriatricsShengJing Hospital of China Medical UniversityShenyang, Liaoning ProvinceChina
  8. 8.Department of NephrologyKidney Institute of Chinese PLA, Chinese PLA General Hospital, State Key Laboratory of Kidney DiseasesBeijingChina

Personalised recommendations